I don't find many examples of cluster analysis to share, but this example is REALLY engaging (using data to find serial killers), and is simple enough for a baby statistician BUT you can also make it a more advanced lesson as the data's owners freely share their data and code. Short Version: Journalist Thomas Hargrove (and his team) used cluster analysis to find clusters of similar killings within geographic areas. These might be a sign that a serial killer is active in that geographic region. It correctly identified a killer in Indiana. I found this interview from datainnovation.org which most succinctly describes the data analysis: https://www.datainnovation.org/2017/07/5-qs-for-thomas-hargrove-founder-of-the-murder-accountability-project/ Also statsy because the cluster analysis was validated using data from known serial killers. Hargrove's data and code can be accessed  here  and more information on his overall project to solve murders can be found...

I think that language is fascinating. Back when I taught developmental, I always liked to teach how babies learn to talk in sort of the same way all across the world. I like regional difference in American English (for example, swearing and regional colloquialisms ). So, I really like this research that investigates the rise and fall of slang in America. And I think it could be used in a statistics class. How to use in class? 1. Funny list of descriptive statistics. 2. Research methodology for using Google searches to answer a question. A good opening for discussion of archival data, data mining, and creating inclusion criteria for research methodology. 3. Using graphs to illustrate trends across time. This feature is interactive. 4. Further interactive features demonstrating how heat maps can be used to demonstrate state-by-state popularity over time. Here, "dank memes" peaked in April 2016 in Montana. 5. The author eye-balled the data can came up ...